Triple
T6064156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lori |
E135112
|
entity |
| Predicate | hasNameDayLanguageContext |
P57867
|
FINISHED |
| Object | English-speaking countries |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: English-speaking countries | Statement: [Lori, hasNameDayLanguageContext, English-speaking countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameDayLanguageContext Context triple: [Lori, hasNameDayLanguageContext, English-speaking countries]
-
A.
hasNameDayContext
chosen
Indicates that an entity’s name day is interpreted or celebrated within a specific contextual framework (such as culture, calendar system, or tradition).
-
B.
hasNameDayRelation
Indicates a relationship where a person’s name is associated with a specific name day or feast day in a calendar.
-
C.
hasNameDay
Indicates that an entity is associated with a specific date on which its name is traditionally celebrated (a name day).
-
D.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
E.
hasDayNameSystem
Indicates that an entity employs or is associated with a particular system for naming or designating days.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05723c91c819090b4d4672e72f9f3 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049f031408190b08b2766237c5dd0 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.